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Fuzzy Logic User Adaptive Navigation Control System For Mobile Robots In Unknown Environments

机译:未知环境下移动机器人的模糊逻辑用户自适应导航控制系统

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摘要

This paper presents a software implementation of a user adaptive fuzzy control system for autonomous navigation in mobile robots for unknown environments. This system has been tested in a pioneer mobile robot and on a robotic wheelchair, fitted with PLS laser sensor to detect the obstacles and odometry sensors for localization of robots and the goal positions. The system is able to drive the robots to their goal position avoiding static and dynamic obstacles, without using any pre-built map. Our approach learn from user behaviors in the way it can resolve different situations against obstacles or walls.We propose and implement two updates for the fuzzy system. For the implementation of the learning algorithm we use a weighting scheme giving a value for each fuzzy-rule, this value is based on the synapse-weight idea and represent the contribution of each rule in the system output. We also create of a more important sector in the definition of the fuzzy-variables, based on a statistics system that measure the uses of all the sets of the variables in order to contract the size of the rule-base.
机译:本文介绍了用于未知环境中移动机器人自主导航的用户自适应模糊控制系统的软件实现。该系统已在先锋移动机器人和机器人轮椅上进行了测试,该轮椅配有PLS激光传感器以检测障碍物和里程计传感器,以定位机器人和目标位置。该系统无需使用任何预先构建的地图即可将机器人驱动到目标位置,从而避免了静态和动态障碍。我们的方法从用户行为中学习如何解决障碍或墙壁的不同情况。我们建议并实施两个模糊系统更新。对于学习算法的实现,我们使用加权方案为每个模糊规则提供一个值,该值基于突触加权思想,并表示每个规则在系统输出中的贡献。我们还基于统计系统创建了一个在模糊变量定义中更重要的部门,该统计系统测量所有变量集的使用以收缩规则库的大小。

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